---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Final_VietNam-aug_insert_synonym
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# xlm-roberta-base-Final_VietNam-aug_insert_synonym

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0797
- Accuracy: 0.76
- F1: 0.7646

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0701        | 1.0   | 87   | 1.0366          | 0.52     | 0.4318 |
| 0.867         | 2.0   | 174  | 0.7789          | 0.68     | 0.6607 |
| 0.6041        | 3.0   | 261  | 0.7027          | 0.71     | 0.7149 |
| 0.4334        | 4.0   | 348  | 0.7618          | 0.74     | 0.7429 |
| 0.3054        | 5.0   | 435  | 0.7701          | 0.72     | 0.7208 |
| 0.2288        | 6.0   | 522  | 0.9844          | 0.72     | 0.7249 |
| 0.1817        | 7.0   | 609  | 1.0040          | 0.73     | 0.7358 |
| 0.1369        | 8.0   | 696  | 1.0797          | 0.76     | 0.7646 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3